2025-04-02 12:13:07,436 - INFO - Num classes: 3
2025-04-02 12:18:55,993 - INFO - Class weights: tensor([0.5161, 4.2842, 1.2065], device='cuda:0')
2025-04-02 12:18:55,996 - INFO - Model architecture:
HyperspectralLogisticRegressionModel(
  (linear): Linear(in_features=1080, out_features=3, bias=True)
)
2025-04-02 12:18:55,996 - INFO - Using cuda device
2025-04-02 12:28:13,294 - INFO - Epoch: 0/100. Training time: 365.764
2025-04-02 12:28:13,297 - INFO - Training Metrics...
2025-04-02 12:28:13,297 - INFO - {'loss': 2.0600432677146716, 'f1': 44.16659240014248, 'acc': 55.437552124215074, 'precision': 48.39512968856828, 'recall': 50.7716642087225, 'balanced acc': 50.7716642087225}
2025-04-02 12:28:13,298 - INFO - Validation Metrics... Inference time: 191.524
2025-04-02 12:28:13,298 - INFO - {'loss': 1.857227965246273, 'f1': 46.69768734101188, 'acc': 52.954334918302756, 'precision': 48.46169493557176, 'recall': 47.289691741797554, 'balanced acc': 47.289691741797554}
2025-04-02 12:28:13,298 - INFO - ==================================================
2025-04-02 13:15:22,386 - INFO - Epoch: 5/100. Training time: 369.173
2025-04-02 13:15:22,389 - INFO - Training Metrics...
2025-04-02 13:15:22,389 - INFO - {'loss': 1.0438756958032265, 'f1': 55.054493030573816, 'acc': 67.13024001667975, 'precision': 57.39087589577788, 'recall': 61.529904566348634, 'balanced acc': 61.529904566348634}
2025-04-02 13:15:22,389 - INFO - Validation Metrics... Inference time: 194.776
2025-04-02 13:15:22,389 - INFO - {'loss': 0.9286399091346355, 'f1': 56.84970953906414, 'acc': 60.41844101168948, 'precision': 60.211988805696414, 'recall': 62.61693925523173, 'balanced acc': 62.61693925523173}
2025-04-02 13:15:22,389 - INFO - ==================================================
2025-04-02 14:04:26,450 - INFO - Epoch: 10/100. Training time: 394.214
2025-04-02 14:04:26,453 - INFO - Training Metrics...
2025-04-02 14:04:26,453 - INFO - {'loss': 0.9075851761377774, 'f1': 54.53523556824502, 'acc': 67.14438254268053, 'precision': 56.02225577267394, 'recall': 59.8952837614252, 'balanced acc': 59.8952837614252}
2025-04-02 14:04:26,453 - INFO - Validation Metrics... Inference time: 231.834
2025-04-02 14:04:26,453 - INFO - {'loss': 1.004958597919609, 'f1': 53.26220478334221, 'acc': 60.51481065131748, 'precision': 54.983454398103234, 'recall': 53.33413118984775, 'balanced acc': 53.33413118984775}
2025-04-02 14:04:26,453 - INFO - ==================================================
2025-04-02 14:52:17,659 - INFO - Epoch: 15/100. Training time: 364.640
2025-04-02 14:52:17,661 - INFO - Training Metrics...
2025-04-02 14:52:17,662 - INFO - {'loss': 0.9771131598032438, 'f1': 54.730999220883845, 'acc': 64.87393860789507, 'precision': 58.29115454229711, 'recall': 61.3841804576172, 'balanced acc': 61.3841804576172}
2025-04-02 14:52:17,662 - INFO - Validation Metrics... Inference time: 195.186
2025-04-02 14:52:17,662 - INFO - {'loss': 0.8493177634251269, 'f1': 61.15331744967135, 'acc': 67.71760870091708, 'precision': 61.42463124493218, 'recall': 63.02436137854699, 'balanced acc': 63.02436137854699}
2025-04-02 14:52:17,662 - INFO - ==================================================
2025-04-02 15:42:34,275 - INFO - Epoch: 20/100. Training time: 416.370
2025-04-02 15:42:34,278 - INFO - Training Metrics...
2025-04-02 15:42:34,279 - INFO - {'loss': 0.989556107765589, 'f1': 52.149466548978495, 'acc': 63.496990593112244, 'precision': 54.196486967260796, 'recall': 60.45557323798467, 'balanced acc': 60.45557323798467}
2025-04-02 15:42:34,279 - INFO - Validation Metrics... Inference time: 240.019
2025-04-02 15:42:34,279 - INFO - {'loss': 0.7596950976154472, 'f1': 61.91348548717329, 'acc': 68.35137783357014, 'precision': 61.81648929621251, 'recall': 64.30346314259309, 'balanced acc': 64.30346314259309}
2025-04-02 15:42:34,280 - INFO - ==================================================
2025-04-02 16:38:11,527 - INFO - Epoch: 25/100. Training time: 371.070
2025-04-02 16:38:11,529 - INFO - Training Metrics...
2025-04-02 16:38:11,529 - INFO - {'loss': 1.0885713222699287, 'f1': 53.190616697287076, 'acc': 63.17493193190737, 'precision': 56.52905948736711, 'recall': 59.63156836660581, 'balanced acc': 59.63156836660581}
2025-04-02 16:38:11,530 - INFO - Validation Metrics... Inference time: 194.866
2025-04-02 16:38:11,530 - INFO - {'loss': 0.8368852395045606, 'f1': 61.44671345660283, 'acc': 67.02407525510205, 'precision': 61.23206680170512, 'recall': 64.31614226582579, 'balanced acc': 64.31614226582579}
2025-04-02 16:38:11,530 - INFO - ==================================================
2025-04-02 17:24:26,273 - INFO - Epoch: 30/100. Training time: 361.767
2025-04-02 17:24:26,276 - INFO - Training Metrics...
2025-04-02 17:24:26,276 - INFO - {'loss': 0.8129701201732342, 'f1': 57.25886701337848, 'acc': 66.11417553800366, 'precision': 61.14499796368327, 'recall': 65.34021208418449, 'balanced acc': 65.34021208418449}
2025-04-02 17:24:26,276 - INFO - Validation Metrics... Inference time: 189.077
2025-04-02 17:24:26,277 - INFO - {'loss': 0.8884238170672066, 'f1': 59.87691614428626, 'acc': 66.92442602040816, 'precision': 60.14418551603088, 'recall': 61.640903498305335, 'balanced acc': 61.640903498305335}
2025-04-02 17:24:26,277 - INFO - ==================================================
2025-04-02 18:10:24,919 - INFO - Epoch: 35/100. Training time: 360.484
2025-04-02 18:10:24,922 - INFO - Training Metrics...
2025-04-02 18:10:24,922 - INFO - {'loss': 0.9407154566202408, 'f1': 54.49998881927651, 'acc': 65.65366831828885, 'precision': 57.654647055380394, 'recall': 64.38763861244108, 'balanced acc': 64.38763861244108}
2025-04-02 18:10:24,922 - INFO - Validation Metrics... Inference time: 192.750
2025-04-02 18:10:24,922 - INFO - {'loss': 0.9382188742673849, 'f1': 56.58697073883501, 'acc': 61.38516472649186, 'precision': 57.47721448312352, 'recall': 58.87191746209197, 'balanced acc': 58.87191746209197}
2025-04-02 18:10:24,923 - INFO - ==================================================
2025-04-02 18:55:53,032 - INFO - Epoch: 40/100. Training time: 358.290
2025-04-02 18:55:53,035 - INFO - Training Metrics...
2025-04-02 18:55:53,035 - INFO - {'loss': 0.8391717443099389, 'f1': 56.82543308470858, 'acc': 69.85979863700288, 'precision': 57.93105383965138, 'recall': 64.14301885218613, 'balanced acc': 64.14301885218613}
2025-04-02 18:55:53,035 - INFO - Validation Metrics... Inference time: 187.219
2025-04-02 18:55:53,036 - INFO - {'loss': 1.4593198842640165, 'f1': 51.88480196408247, 'acc': 56.62046810417205, 'precision': 56.20968872140884, 'recall': 55.02047999330002, 'balanced acc': 55.02047999330002}
2025-04-02 18:55:53,036 - INFO - ==================================================
2025-04-02 19:41:34,798 - INFO - Epoch: 45/100. Training time: 358.202
2025-04-02 19:41:34,801 - INFO - Training Metrics...
2025-04-02 19:41:34,801 - INFO - {'loss': 0.8788274648862008, 'f1': 57.68480939663376, 'acc': 69.99953752534668, 'precision': 60.09301999849359, 'recall': 63.55234953572829, 'balanced acc': 63.55234953572829}
2025-04-02 19:41:34,801 - INFO - Validation Metrics... Inference time: 191.421
2025-04-02 19:41:34,801 - INFO - {'loss': 0.959729067886932, 'f1': 59.214777382797635, 'acc': 64.52479676601654, 'precision': 60.90187225941843, 'recall': 62.942993592363116, 'balanced acc': 62.942993592363116}
2025-04-02 19:41:34,801 - INFO - ==================================================
2025-04-02 20:27:34,572 - INFO - Epoch: 50/100. Training time: 360.116
2025-04-02 20:27:34,574 - INFO - Training Metrics...
2025-04-02 20:27:34,575 - INFO - {'loss': 0.7670110953159821, 'f1': 58.155769768991064, 'acc': 68.80400221987834, 'precision': 60.40119491101786, 'recall': 66.1554746681859, 'balanced acc': 66.1554746681859}
2025-04-02 20:27:34,575 - INFO - Validation Metrics... Inference time: 192.228
2025-04-02 20:27:34,575 - INFO - {'loss': 0.7437652455100531, 'f1': 55.49289965142379, 'acc': 68.52570092514854, 'precision': 57.188695437319396, 'recall': 56.24049902314161, 'balanced acc': 56.24049902314161}
2025-04-02 20:27:34,575 - INFO - ==================================================
2025-04-02 21:14:01,895 - INFO - Epoch: 55/100. Training time: 365.048
2025-04-02 21:14:01,898 - INFO - Training Metrics...
2025-04-02 21:14:01,898 - INFO - {'loss': 0.9495210617016523, 'f1': 56.5260649145843, 'acc': 66.55856002256671, 'precision': 59.906846547381164, 'recall': 64.25063804705601, 'balanced acc': 64.25063804705601}
2025-04-02 21:14:01,898 - INFO - Validation Metrics... Inference time: 193.245
2025-04-02 21:14:01,898 - INFO - {'loss': 0.7615955947320673, 'f1': 62.34034710053686, 'acc': 69.01312443490055, 'precision': 62.650431094576206, 'recall': 64.50748775722947, 'balanced acc': 64.50748775722947}
2025-04-02 21:14:01,898 - INFO - ==================================================
2025-04-02 22:00:01,782 - INFO - Epoch: 60/100. Training time: 359.127
2025-04-02 22:00:01,784 - INFO - Training Metrics...
2025-04-02 22:00:01,785 - INFO - {'loss': 0.7397096095941006, 'f1': 60.41197465845557, 'acc': 70.47892699748168, 'precision': 63.744413091640375, 'recall': 68.60060699947744, 'balanced acc': 68.60060699947744}
2025-04-02 22:00:01,785 - INFO - Validation Metrics... Inference time: 194.340
2025-04-02 22:00:01,785 - INFO - {'loss': 0.7961088388781005, 'f1': 59.73307118118104, 'acc': 67.9818179249548, 'precision': 61.9571207069397, 'recall': 61.218582313172206, 'balanced acc': 61.218582313172206}
2025-04-02 22:00:01,785 - INFO - ==================================================
2025-04-02 22:45:48,479 - INFO - Epoch: 65/100. Training time: 358.058
2025-04-02 22:45:48,481 - INFO - Training Metrics...
2025-04-02 22:45:48,482 - INFO - {'loss': 0.7579393157592187, 'f1': 60.81572768567845, 'acc': 69.34634956747122, 'precision': 63.44736864462772, 'recall': 68.92111794486055, 'balanced acc': 68.92111794486055}
2025-04-02 22:45:48,482 - INFO - Validation Metrics... Inference time: 187.875
2025-04-02 22:45:48,482 - INFO - {'loss': 0.8496747243253491, 'f1': 58.875523141887406, 'acc': 66.71665105915784, 'precision': 61.484925782607306, 'recall': 60.79617628057895, 'balanced acc': 60.79617628057895}
2025-04-02 22:45:48,482 - INFO - ==================================================
2025-04-02 23:31:20,993 - INFO - Epoch: 70/100. Training time: 359.876
2025-04-02 23:31:20,996 - INFO - Training Metrics...
2025-04-02 23:31:20,996 - INFO - {'loss': 0.7413350679935553, 'f1': 58.91336455705498, 'acc': 71.2270116880887, 'precision': 61.56039603723686, 'recall': 65.99856719420602, 'balanced acc': 65.99856719420602}
2025-04-02 23:31:20,997 - INFO - Validation Metrics... Inference time: 187.900
2025-04-02 23:31:20,997 - INFO - {'loss': 0.8458632962613166, 'f1': 63.483207352451096, 'acc': 68.06375734629296, 'precision': 64.6216433315146, 'recall': 68.20791801425771, 'balanced acc': 68.20791801425771}
2025-04-02 23:31:20,997 - INFO - ==================================================
2025-04-03 00:17:23,527 - INFO - Epoch: 75/100. Training time: 364.689
2025-04-03 00:17:23,530 - INFO - Training Metrics...
2025-04-03 00:17:23,530 - INFO - {'loss': 0.6811980803807577, 'f1': 63.680910612244446, 'acc': 74.0291226165947, 'precision': 65.46887668461994, 'recall': 73.31351610077206, 'balanced acc': 73.31351610077206}
2025-04-03 00:17:23,530 - INFO - Validation Metrics... Inference time: 192.792
2025-04-03 00:17:23,531 - INFO - {'loss': 0.804144344752348, 'f1': 63.48499656061226, 'acc': 68.4351336460217, 'precision': 64.20915182882804, 'recall': 67.65091881316557, 'balanced acc': 67.65091881316557}
2025-04-03 00:17:23,531 - INFO - ==================================================
2025-04-03 01:03:52,623 - INFO - Epoch: 80/100. Training time: 361.180
2025-04-03 01:03:52,626 - INFO - Training Metrics...
2025-04-03 01:03:52,626 - INFO - {'loss': 0.6982723474502563, 'f1': 62.96216831983621, 'acc': 73.41527055533751, 'precision': 65.28453166491765, 'recall': 71.63542899246758, 'balanced acc': 71.63542899246758}
2025-04-03 01:03:52,626 - INFO - Validation Metrics... Inference time: 188.164
2025-04-03 01:03:52,626 - INFO - {'loss': 0.8068166307256192, 'f1': 64.13158158723022, 'acc': 68.91014514983208, 'precision': 64.8573393813945, 'recall': 68.67254796634958, 'balanced acc': 68.67254796634958}
2025-04-03 01:03:52,626 - INFO - ==================================================
2025-04-03 01:49:50,834 - INFO - Epoch: 85/100. Training time: 361.082
2025-04-03 01:49:50,837 - INFO - Training Metrics...
2025-04-03 01:49:50,837 - INFO - {'loss': 0.7432091022149111, 'f1': 61.53389857968165, 'acc': 72.72694985446103, 'precision': 63.32689546034591, 'recall': 68.23185248044612, 'balanced acc': 68.23185248044612}
2025-04-03 01:49:50,837 - INFO - Validation Metrics... Inference time: 191.984
2025-04-03 01:49:50,838 - INFO - {'loss': 0.8005127439016029, 'f1': 62.87213974780781, 'acc': 67.56356864343839, 'precision': 64.46427586118118, 'recall': 67.68133411142881, 'balanced acc': 67.68133411142881}
2025-04-03 01:49:50,838 - INFO - ==================================================
2025-04-03 02:26:36,782 - INFO - Early stopping criterion met. Stopping training.
2025-04-03 02:26:37,490 - INFO - Initializing final Evaluations:

2025-04-03 02:29:44,182 - INFO - Final validation metrics:
{'f1': 67.16067907456758, 'acc': 71.26766944910877, 'precision': 66.52729261615714, 'recall': 69.78592874721346, 'balanced acc': 69.78592874721346}
2025-04-03 02:30:04,285 - INFO - Final test pixel-wise classification metrics:
{'f1': 67.50421458774358, 'acc': 75.10857275871243, 'precision': 72.99465614683619, 'recall': 67.9676225484883, 'balanced acc': 67.9676225484883}
2025-04-05 02:08:02,307 - INFO - Num classes: 3
2025-04-05 02:08:02,310 - INFO - Class weights: None
2025-04-05 02:08:02,424 - INFO - Model architecture:
HyperspectralLogisticRegressionModel(
  (linear): Linear(in_features=1080, out_features=3, bias=True)
)
2025-04-05 02:08:02,424 - INFO - Using cuda device
2025-04-05 02:08:02,426 - INFO - Initializing final Evaluations:

2025-04-05 02:08:46,882 - INFO - Num classes: 3
2025-04-05 02:08:46,882 - INFO - Class weights: None
2025-04-05 02:08:46,996 - INFO - Model architecture:
HyperspectralLogisticRegressionModel(
  (linear): Linear(in_features=1080, out_features=3, bias=True)
)
2025-04-05 02:08:46,996 - INFO - Using cuda device
2025-04-05 02:08:46,997 - INFO - Initializing final Evaluations:

2025-04-05 02:08:58,528 - INFO - Num classes: 3
2025-04-05 02:08:58,528 - INFO - Class weights: None
2025-04-05 02:08:58,637 - INFO - Model architecture:
HyperspectralLogisticRegressionModel(
  (linear): Linear(in_features=1080, out_features=3, bias=True)
)
2025-04-05 02:08:58,638 - INFO - Using cuda device
2025-04-05 02:08:58,639 - INFO - Initializing final Evaluations:

2025-04-05 02:15:51,744 - INFO - Num classes: 3
2025-04-05 02:15:51,744 - INFO - Class weights: None
2025-04-05 02:15:51,862 - INFO - Model architecture:
HyperspectralLogisticRegressionModel(
  (linear): Linear(in_features=1080, out_features=3, bias=True)
)
2025-04-05 02:15:51,862 - INFO - Using cuda device
2025-04-05 02:15:51,863 - INFO - Initializing final Evaluations:

